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Xianghui Yin

dblp:324/6336 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
grasping
0.612022
TaTa: A Universal Jamming Gripper with High-Quality Tactile Perception and Its Application to Underwater Manipulation · ICRA 2022
Robotics › Robot manipulation › grasping › soft gripper
jamming gripper
0.612022
TaTa: A Universal Jamming Gripper with High-Quality Tactile Perception and Its Application to Underwater Manipulation · ICRA 2022
Robotics › Robot manipulation
tactile sensing
0.612022
TaTa: A Universal Jamming Gripper with High-Quality Tactile Perception and Its Application to Underwater Manipulation · ICRA 2022
Robotics › Robot manipulation › tactile sensing
vision-based tactile sensing
0.612022
TaTa: A Universal Jamming Gripper with High-Quality Tactile Perception and Its Application to Underwater Manipulation · ICRA 2022
Robotics › Robot manipulation
underwater manipulation
0.212022
TaTa: A Universal Jamming Gripper with High-Quality Tactile Perception and Its Application to Underwater Manipulation · ICRA 2022

Methods — techniques the papers use, named apart from their topics

refractive index matching · 0.6particle jamming · 0.6
YearPublicationVenuePosition
2022 TaTa: A Universal Jamming Gripper with High-Quality Tactile Perception and Its Application to Underwater Manipulation
abstract
Large-area and high-precision tactile sensing information can not only improve the stability of robot grasping but also compensate for the lack of visual information in specific environments such as turbid underwater, dimness, and smoke. In this paper, we devise a universal jamming gripper with high-quality tactile sensing capability. The gripper adopts the particle jamming mechanism for grasping, and simultaneously uses a built-in camera to detect the deformation of its surface to obtain tactile information. To make the inside of the gripper transparent, glass beads and liquid with the same refractive index are applied as the internal filling. Besides, special treatments are taken to improve the tactile perception resolution of the gripper. The design perfectly merges visual-based tactile sensing into the traditional universal jamming gripper without changing its original gripping performance, making it possible for simultaneous grasping and sensing. To verify the tactile perception and grasping ability of the gripper in specific environments, we design two underwater experiments for grasping and pipe leak detection based on tactile information. Both have achieved a success rate not less than 95%, which demonstrates the effectiveness of the proposed gripper for manipulation in low visibility environments.
Shoujie Li, Xianghui Yin, Chongkun Xia, Linqi Ye, Xueqian Wang 0001, Bin Liang 0001
ICRA2